Seismic Acquisition & Processing
The Earth's subsurface can be imaged by a seismic survey, therefore, seismic data acquisition and processing are key components in geophysical exploration. In a seismic survey, elastic acoustic waves are generated by a source at the Earth's surface and the waves are radiated into the Earth's subsurface. For land seismic surveys, the usual source is dynamite or a seismic vibrator, while for a marine seismic survey the source is typically an airgun array.
As the waves radiate downward through the Earth's subsurface, they reflect and propagate upwards towards the surface whenever the subsurface medium changes. The upward reflections are detected by a number of receivers and the reflected data recorded and processed in order to image the subsurface. Interpretation of these acoustic images of the subsurface formation leads to the structural description of the subsurface geological features, such as faults, salt domes, anticlines, or other features indicative of hydrocarbon traps.
While two dimensional ("2D") seismic surveys have been conducted since the 1920's , three dimensional ("3D") seismic surveys have only recently become widely used. 3D surveys more accurately reflect the subsurface positions of the hydrocarbon traps, but are expensive and time consuming to acquire and process. For an offshore 3D data set covering a 20.times.20 km area, it costs about $3 M dollars (1991 dollars) to acquire the data with another $1 M dollars for data processing to transform the raw data into usable images. Because the cost of such a seismic survey is considerably less than the cost of drilling an offshore oil well, 3D seismic surveys are often worth the investment.
One common type of seismic survey is a marine survey, performed by boats in offshore waters. To record seismic data, a boat tows airguns (seismic sources) near its stern, and an up to 5 km long "streamer" containing hydrophones (seismic receivers) along its length. As the boat sails forward, it fires one source and receives a series of echoes into each seismic receiver. For each source-receiver pair, one prestack seismic trace is created. Each trace records sound waves that echo from abrupt acoustic impedance changes in rock beneath the ocean floor. Also recorded in a prestack trace, in a header section of the trace record, is information about the location of the source and receiver [Barry, Cavers, and Kneale, 1975]. Prestack traces are not associated with any particular area of the survey. Each echo that appears in a prestack trace is caused by a reflector that lies somewhere along, and tangent to, an elliptical path whose foci are the seismic source and receiver.
The spatial relationship between sources and receivers in a land seismic acquisition scenario differs from that described above; however, the present invention is unaffected by this.
A seismic survey is performed over a bounded region of the earth. This region is generally, but not necessarily precisely, rectangular. The survey area is partitioned into an array of bins. "Binning" is the assignment of traces to a survey array--usually a 12.5 by 25 meter rectangle. Any particular bin is located by its Cartesian coordinates in this array (i.e., by its row and column number). The ultimate output of the seismic survey is data that shows the location and strength of seismic reflectors in each bin, as a function of depth or time. This information cannot be deduced directly, but rather must be computed by applying numerous data processing steps to data recorded.
Although 3D marine surveys vary widely in size (1,000 to 100,000 km.sup.2), a typical marine survey might generate in excess of 40,000 data acquisition tapes. Data is accumulated at a staggering rate, about 1.5 million data samples every 10 seconds. A significant amount of time and money is spent in processing this enormous amount of data. The result of the seismic survey is thus an enormous amount of raw data indicative of reflected signals which are a function of travel time, propagation, and reflection effects. The goal is to present the reflected amplitudes as a function of lateral position and depth.
A typical marine seismic survey goes through three distinct sequential stages--data acquisition, data processing, and data interpretation. Data processing is by far the most time consuming process of the three. The acquisition time for a medium to large 3D marine seismic survey is in the order of two months. In addition to seismic data, navigation information is also recorded for accurate positioning of the sources and receivers. The resulting digital data must be rendered suitable for interpretation purposes by processing the data at an onshore processing center. The processing sequence can be divided into the following five processing steps.
1. Quality Control, filtering and deconvolution. This processing is applied on a trace basis to filter noise, sharpen the recorded response, suppress multiple echoes, and generally improve the signal-to-noise ratio. Most of these signal processing operations can be highly vectorized. PA1 2. Velocity analyses for migration. This processing estimates the velocity of the subsurface formations from the recorded data by modeling the propagation of acoustic waves with estimated velocities and checking for signal coherence in the acquired data. It is similar to migration but is applied to a small section of the data cube. PA1 3. 3D dip moveout correction and stacking. This processing step, generally the most input/output intensive part of the processing, (i) sums together several traces in order to eliminate redundancy and increase the signal-to-noise ratio, (ii) corrects for time delays that occur when the reflected signal is recorded by successive hydrophones that are located increasingly farther away from the energy source, and (iii) positions and orients the stacked data in accordance with the navigation information. After this processing step, the data is referred to as stacked data. This step normally constitutes on the order of a 100 to 1 reduction in data volume. Migration. This processing step, computationally the most intensive, relocates the position of reflected strata, that are recorded in time, to their correct position in depth. PA1 5. Enhancement and filtering. This processing step is used to enhance the migrated data using digital filtering techniques.
The stacking process (step 3) reduces the amount of data to what is essentially a three dimensional array of numbers (i.e. a data cube) representing amplitudes of reflected seismic waves recorded over a period of time (usually 8 seconds). Such data cubes can be large, for example, a medium size 3D survey may produce cubes as large as 1000.times.1000.times.2000 of floating-point numbers.
The stacked data cube represents a surface recording of acoustic echoes returned from the earth interior and is not usually directly interpretable. The migration (or acoustic imaging process, step 4) is used to convert stacked data into an image or a map which can then be viewed as a true depth map cut out of the survey area.
Thus, migration is one of the most critical and most time consuming components in seismic processing is migration. Generally speaking, migration transforms the seismic data recorded as a function of time into data positioned as a function of depth fusing preliminary knowledge of the propagation velocities of the subsurface. In particular, migration moves dipping reflectors to their true subsurface position. Migration is typically performed on post stack seismic data to reduce the amount of processing time, but even so takes weeks of conventional supercomputer time for even medium size post stack seismic data cubes.
Many types of stacking and migration processes are well known. See, O. Yilmaz. 1987. Seismic Data Processing. Tulsa, Okla.: Society of Exploration Geophysicists. Usually, one poststack trace is associated with each bin. However, it is also possible to create multiple poststack traces per bin. For example, each such trace might contain contributions from prestack traces whose source-receiver separation falls within a specific range. (In this case, the bin is said to contain a common depth-point or common midpoint gather.)
Stacking programs create poststack data from prestack data by simple manipulation of prestack data. In general, a stacking program transforms each prestack trace exactly once. Migration programs create poststack data from prestack data by more complicated, computationally intensive, manipulation of the same data. Migration programs transform each prestack trace a large number of times, requiring commensurately more computation than simpler stacking programs. Multiple prestack traces are transformed and added together and superimposed to create the one or more poststack traces associated with a bin.
One common approach to implementing migration computations is the Kirchhoff method. See, U.S. Pat. No. 5,198,979 Moorhead et al. See also, S. Deregowski and F. Rocca, 1981. Geometrical optics and wave theory for constant-offset sections in layered media. Geophysical Prospecting, 29, 374-387. Using the Kirchhoff approach to implement 3D Dip Moveout ("DMO"), a program transforms a prestack trace once for each bin that lies under a line drawn between the seismic source and receiver. This line is referred to as the "coverage" of the trace. Each transformed prestack trace is added, sample-by-sample, to incrementally create one or more the poststack traces in each bin. The signal-to-noise ratio of each poststack trace increases as the square root of the number of transformed prestack traces added together to form it.
The Kirchhoff approach is computationally expensive. Approximately 30 arithmetic operations (floating-point operations, or FLOPs) are required for each sample of each transformed trace in DMO. Given an average shot-receiver separation of 3 kilometers, a bin width of 12.5 meters, and 8 seconds worth of data in each trace acquired at 4ms/sample, this implies an average of approximately 10 million FLOPs per trace. A typical 20 km square marine survey using 12.5 meter wide, 25 meter tall bins contains perhaps 80 million prestack traces. The DMO process thus consumes approximately 800 trillion FLOPs. This computational expense motivates the implementation of migration programs such as DMO on some form of high-performance supercomputer, such as a massively parallel processor. See, Thinking Machines Corporation, 1993. The Connection Machine CM-5 Technical Summary. Such a processor is an attractive platform upon which to execute migration programs, because its performance scales up as its size increases; thus, the system can grow incrementally as the computational demand of the processing organization increases. See also, W. Daniel Hillis and Lewis W. Tucker, The CM-5 Connection Machine: A scalable supercomputer, Communications of the ACM, November 1993, Vol. 36, No. 11, pp 31-40.
Parallel Computation
FIG. 1 is an example of a multiprocessor parallel computer, specifically a massively parallel processor (MPP) such as the CM-5. In FIG. 1, an MPP 10 consists of 3 major components: (i) a disk storage system 12 whose capacity and data transfer rate can be scaled up as storage and data throughput requirements demand, (ii) a data and control communications network 14 that ties together the processors and the disk storage system, and (iii) a set of processing nodes 16 (see FIG. 2), each containing at least one processor 18, memory 20, and interface 22 to the data and control network 14. The capacity of the data network 14 (the amount of data it can transport in a given amount of time) scales as the number of nodes 16 increases. The size of the set of processing nodes 16 can be scaled up as computational requirements demand. On an MPP, processor nodes 16 can execute independently from one another; however, the control portion of the data and control communications network 14 provides a means by which all nodes 16 can synchronize their activities.
An MPP can improve the performance of computationally-intensive migration programs because it is possible to partition the work to be done and assign a part of it to each processor node 16. For this approach to scale as the size of the MPP 10 scales, the work partitions must be truly independent of one another, such that no two processors share work. This is an expression of Amdahl's Law, which states that the maximum parallelization speedup possible is the inverse of the fraction of time an application spends performing serial computation. See, G. Fox et al., 1988. Solving Problems on Concurrent Processors, Vol. 1, page 57.
For example, in seismic migration processing, each bin in the survey area must be assigned to one and only one processor at any one time. Any attempt to assign the same bin to more than a single processor would require a serializing synchronization to guarantee proper results. Because DMO moves a large amount of data, the means by which data is moved between the disk storage system 12 and the memories 20 of the processing nodes 16 is especially important. In order to avoid implications of Amdahl's Law, the data must be moved in parallel as efficiently as possible. One type of disk storage system that satisfies this requirement is a RAID disk system. See, S. J. Lo Verso, M. Isman, A. Nanopoulos, W. Nesheim, E. D. Milne, and R. Wheeler. SFS: A parallel file system for the CM-5. In Proceedings of the 1993 Usenix Conference.
Another implication of Amdahl's Law is that the work partitions must be designed so that all nodes are required to perform equal amounts of computation. This latter requirement is referred to as load balancing.
Kirchhoff DMO on a Multiprocessor
A scalable means to implement DMO on a multiprocessor computer is to: (i) load a set of prestack traces from the disk storage system 12 into the processing nodes 16, (ii) determine which bins in the survey area are covered by the union of all of the loaded traces, (iii) assign to each node 16 a portion of the survey area covered by the loaded traces, (iv) load from the disk system 12 into the appropriate nodes 16 the poststack traces from the covered bins, (v) apply the DMO operator to each loaded prestack trace in each processor to update the poststack traces, and (vi) write out the updated poststack traces from the nodes 16 to the disk system 12. U.S. patent application Ser. No. 08/160,123 filed Dec. 1, 1993 describes a method for inputting seismic data for processing on a multiprocessor computer.
The assignment of portions of the survey area to the nodes 16 must be non-overlapping. This satisfies the independence requirement for scalability on an MPP because each bin is independent of other bins. This also permits a disk I/O strategy that allows the poststack traces to be read from and written to the disk storage system 12 in parallel. This is important, because each poststack trace will typically be read in, updated, and written out many times during the processing of a prestack data set. Thus, the organization of the file on the disk storage system containing the poststack data and the strategy with which the data is read and written can strongly impact the efficiency of the DMO process.
However, a simple non-overlapping partitioning of bins does not in itself guarantee good performance. For example, if each node is a priori assigned the same number of bins to process, this approach will not in general achieve good load balancing. This is especially true when marine seismic data is being processed, due to the geometry with which the data is acquired.
FIG. 3 depicts a typical configuration of seismic sources and receivers in a marine seismic survey. A seismic acquisition vessel 30 sails forward towing a streamer cable 32 containing multiple seismic receivers 36 located at different points along the cable. Near the stern of the vessel is a pair of airguns 34, which are the seismic sources. With each firing of an airgun, a collection of prestack seismic traces are recorded, one-trace from each receiver 36. For each trace and each bin 38 under the coverage of the, the DMO operator transforms the trace and adds it to the poststack trace associated with the bin. Since the stream cable 32 follows in a nearly perfect straight line behind the vessel 30 parallel to the direction the vessel is sailing, the bins closest to the airguns 34 (called "near offset" bins) and under the streamer cable will be in the coverage of more traces than the bins closest to the last receiver 36 on the cable (called "far offset" bins).
The ratio of traces covering a so-called "near offset" bin to those covering a "far offset" bin will be equal to the number of uniquely located receivers 36 on the streamer cable. Typically, there are between 120 and 240 receivers on a cable. This means that a processor node 16 assigned to process a near-offset bin will have perhaps 240 times more work to do than a node assigned to a far-offset bin.
The preceding discussion considered only the processing of a single shot record (the set of traces recorded by all of the receivers from a single shot of an airgun). The load imbalance problem is further exacerbated when multiple shots are processed simultaneously, as is typically done when executing DMO on a multiprocessor computer. To see why this is so, consider that the acquisition vessel sails forward a short distance (typically 25 meters) between shots. As a result, the number of traces covering bins near the near-offset bin of the first shot in a set of shots is multiplied roughly by the size of this set; however, the coverage of the first far-offset bin is unchanged, since the receiver at the end of the streamer cable has now been towed beyond the bin.
A similar load imbalance will exist when processing land seismic data, which is typically sorted into collections of prestack traces associated with each receiver point in the survey. The corresponding shot points are located in all directions and at various distances from the receiver, causing the trace coverage of bins near the receiver to be higher than those farther from the receiver. If sets of traces from multiple receivers are processed simultaneously, and if the receivers in the set are located near one another, the severity load imbalance problem will increase, as it does when multiple marine shot gathers are processed.
In this application, all references to patents are incorporated by reference and all other references are incorporated by reference for background.